Data Engineering Specialist – AI

Bright Vision Technologies; Fishers (IN); Remote; USD 100,000 - 150,000; Full time

Job summary

Bright Vision Technologies is seeking a Data Engineering Specialist – AI to design and operate large-scale data systems that power AI training pipelines. You will focus on ingestion, transformation, quality assurance, data lineage, and high-throughput delivery to training jobs across modalities.

The ideal candidate has 6+ years of data engineering experience, strong Python and JVM language skills, and hands-on experience with petabyte-scale storage and pipelines.

Qualifications

• 6+ years of data engineering experience, with significant work supporting ML or AI workloads.
• Strong proficiency in Python and at least one JVM language.
• Deep experience with modern data processing frameworks such as Spark, Ray, or Beam.
• Hands-on experience operating petabyte-scale storage and pipeline systems.

Responsibilities

• Build and operate petabyte-scale data systems powering AI pipelines.
• Develop ingestion, transformation, quality assurance, lineage for data workflows.
• Improve data infrastructure to boost model training efficiency.

Skills

Python

Java / JVM language

Spark / Ray / Beam

Petabyte-scale data systems

Tools

Spark

Beam

Ray

Job description

Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States. This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential.

Job Title

Data Engineering Specialist – AI

Location

100% Remote Role

Position Type

Full-time (Only W2 candidates)

Salary Range

$100,000–$150,000 Annually

Experience Required

6+ years

Sponsorship

U.S. Citizens, Green Card Holders, EAD Holders, and H-1B transfer candidates are encouraged to apply. We are unable to sponsor new H-1B visa petitions for this position.

Job Summary

We are seeking anData Engineering Specialist – AI to build and operate the large‑scale data systems that power modern AI training and evaluation pipelines. The role combines deep data engineering expertise with a strong understanding of AI workloads, focusing on ingestion, transformation, quality assurance, lineage, and high‑throughput delivery of data to training jobs across diverse modalities. The ideal candidate has experience operating petabyte‑scale data systems, strong software engineering fundamentals, and clear understanding of how data infrastructure choices propagate into model quality and training efficiency.

Required Qualifications

• 6+ years of data engineering experience, with significant work supporting ML or AI workloads.
• Strong proficiency in Python and at least one JVM or systems language.
• Deep experience with modern data processing frameworks such as Spark, Ray, or Beam.
• Hands‑on experience operating petabyte‑scale storage and pipeline systems.

Preferred Qualifications

• Experience with multimodal datasets at large scale.
• Familiarity with data quality tooling and dataset evaluation methodology.
• Exposure to privacy‑preserving data systems and regulated data handling.
• Open‑source contributions to data infrastructure projects.
• Experience supporting frontier model training pipelines.

Equal Employment Opportunity (EEO) Statement

Bright Vision Technologies (BV Teck) is committed to equal employment opportunity (EEO) for all employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other protected status as defined by applicable federal, state, or local laws. This commitment extends to all aspects of employment, including recruitment, hiring, training, compensation, promotion, transfer, leaves of absence, termination, layoffs, and recall.

BV Teck expressly prohibits any form of workplace harassment or discrimination. Any improper interference with employees' ability to perform their job duties may result in disciplinary action up to and including termination of employment.